期刊文献+

熔模铸造工艺集成计算平台开发与应用 被引量:2

Development and Application of Integrated Computational Platform for Investment Casting Processes
原文传递
导出
摘要 目前,熔模铸造工艺优化主要依托于经验试错,存在寻优周期长、人力成本高、操作效率低且缺乏算法优化等问题。构建了基于ProCAST有限元仿真软件和多任务批处理技术的熔模铸造工艺集成计算平台,该平台集成了试验设计算法(DOE)、有限元仿真、结果数据自动读写提取、近似模型构建、多目标优化协同工作等功能。以涡轮导向器为例,铸件缩松量为目标值,浇注温度、环境温度、热辐射率为设计变量,实现了铸造工艺-缺陷快速仿真集成优化。与传统仿真优化相比,使用集成计算平台效率提升了91.66%。 Currently,the optimization of investment casting processes heavily relies on empirical trial-and-error methods,resulting in long optimization cycles,high labor costs,low operational efficiency,and a lack of algorithmic optimization.Therefore,an integrated computing platform for investment casting processes was developed based on the Pro‐CAST finite element simulation software and multitasking batch processing technology,which integrates various functions,including Design of Experiments(DOE)algorithms,finite element simulation,automatic extraction of result data,surrogate model construction,and collaborative multi-objective optimization.Taking a turbine guide vane as example,integrated optimization of casting process-defect simulation was realized with shrinkage as target value,pouring temperature,ambient temperature and thermal emissivity as variables.The efficiency of integrated computing platform is improved by 91.66%compared with that of traditional simulation optimization.
作者 魏鹏啸 郭钊 丁正一 吴文云 包超君 秦蓉 汪东红 WEI Pengxiao;GUO Zhao;DING Zhengyi;WU Wenyun;BAO Chaojun;QIN Rong;WANG Donghong(China Aircraft Southern Industry Co.,Ltd.,Chengdu 611730;Shanghai Key Laboratory of Advanced High Temperature Materials and Precision Forming,Shanghai Jiaotong University,Shanghai 200240;School of Materials Science and Engineering,Shanghai University of Engineering Science,Shanghai 201620;Jiashan Xinhai Precision Casting Co.,Ltd.,Jiaxing 314101;State Key Laboratory of Clean and Efficient Turbomachinery Power Equipment,Dongfang Electric Dongfang Turbine Co.,Ltd.,Deyang 618029)
出处 《特种铸造及有色合金》 CAS 北大核心 2024年第7期923-927,共5页 Special Casting & Nonferrous Alloys
基金 国家重点研发计划资助项目(2022YFB3706800) 国家科技重大专项资助项目(J2019-VI-0004-0117) 国家自然科学基金资助项目(52090042)。
关键词 材料基因工程 集成计算材料工程 智能铸造 材料信息学 Materials Genomic Engineering Integrated Computational Materials Engineering Intelligent Cast⁃ing Material Informatics
  • 相关文献

参考文献11

二级参考文献85

共引文献191

同被引文献33

引证文献2

相关作者

内容加载中请稍等...

相关机构

内容加载中请稍等...

相关主题

内容加载中请稍等...

浏览历史

内容加载中请稍等...
;
使用帮助 返回顶部